Framing Pro-Anorexia Discourse on YouTube in South Korea: Social Network and Exponential Random Graph Model Analysis of Video Communities.

BACKGROUND

YouTube, as a participatory platform, allows algorithmic curation and user engagement to shape health information flows. This dynamic amplifies and isolates harmful narratives, producing enclosed "refracted publics." Pro-anorexia (pro-ana) content exemplifies this, glamorizing extreme thinness as self-control and promoting disordered eating while distancing viewers from evidence-based health discourse. Despite concerns about public health consequences, few studies have examined how channel characteristics and framing strategies drive engagement and echo chamber formation.

OBJECTIVE

This study analyzed how pro-ana discourse circulates on YouTube and identified entry points for intervention. It (1) compared pro-ana, anti-pro-ana, and recovery frames by channel type (institutional vs individual) and subscriber scale (mega [≥1,000,000], meso [100,000-999,999], or micro [10,000-99,999]); (2) constructed video-level networks from overlapping commenters to trace discourse clustering over time; and (3) evaluated how frame and channel attributes shape network connectivity and frame-crossing.

METHODS

We collected 489 Korean-language YouTube videos (January 2020-August 2024) using pro-ana keywords and related-video crawling. Each was coded into 3 frames. Channels were classified by operator type and subscriber scale. A weighted commenter-overlap network was built, backbone-extracted, and analyzed through social network analysis. An exponential random graph model tested predictors of intervideo ties.

RESULTS

Of 489 videos, 369 (75.5%) promoted pro-ana content, mostly in micro- and meso-individual channels (361/369, 97.8%). Recovery frames appeared mainly in micro-individual channels (47/52, 90%). Anti-pro-ana frames clustered in institutional channels (46/68, 68%) but remained structurally peripheral. After backbone filtering, the commenter-overlap network comprised 435 videos and 906 edges. The network showed low density (0.96%) and moderate modularity (0.58) with 19 communities, indicating a fragmented, echo chamber-like structure. Longitudinally, density declined while modularity rose, consistent with echo-chamber intensification. The largest community (n=242) was predominantly pro-ana, while recovery-only (n=25) and anti-pro-ana (n=13) communities were peripheral. The exponential random graph model revealed that homophily was strong for anti-pro-ana (odds ratio [OR]=2.20; P<.001) and became significant for pro-ana with channel×frame interactions (OR=3.12; P<.001). Critically, recovery frames in meso-individual channels were associated with greater intervideo connectivity (OR=2.59; P<.001), and anti-pro-ana frames in those channels were also connective (OR=1.55; P=.003).

CONCLUSIONS

Pro-ana discourse on YouTube is fragmented into "refracted publics." Meso-level individual channels using recovery narratives serve as critical bridges across polarized frames. Public health efforts should partner with mid-tier influencers to co-create emotionally resonant recovery content that disrupts echo chambers and fosters cross-frame dialogue.